Quantifying reputation loss of pipeline operator from various stakeholders perspectives, part 1: prioritization

Quantifying reputation loss (RL) due to pipeline damage is commonly generalized based on the owner's definition. This one-way perspective of portraying RL is unfair and unrealistic and consequently miscalculates the impact assessment of pipeline damage; hence, inaccurate risk prediction. It is crucial to develop a model to quantify qualitative RL to avoid unpredicted risk. Thus, this article provides a framework for a procedure to calculate RL by utilizing the factors identified in a previous study. In this paper (Part 1), the prioritization of factors based on the stakeholders' perspectives is presented. The factors were grouped into stakeholder-influenced categories and prioritized by a fuzzy analytic hierarchy process based on the feedback gained from the stakeholders, i.e., investors, customers, employees and the public. The result shows that factor D3, “Accident severity”, was ranked highest by all stakeholders. The priority vector for each factor obtained was assigned as a weight of the factor. The pipeline owner's reputation loss model (RLM) is developed by applying the obtained priority vectors in the subsequent paper (Part 2). The developed model was verified by experts as a comprehensive, clear, objective, practical and moderately reliable model. The model was applied to a case study and eventually produced a lower risk value when compared with the currently used model. It is proven that RL factors can be quantitatively measured and can simultaneously improve pipeline damage impact assessment. Thus, a risk-based inspection schedule can be managed comprehensively

Analysis of luxury resort hotels by using the Fuzzy Analytic Hierarchy Process and the Fuzzy Delphi Method

Experience Economy is an accelerator switching the experience process of consumption into eternal memory, perfecting value and promoting positive after-buying intention. This research uses the Fuzzy Delphi Method (FDM) and Fuzzy Analytic Hierarchy Process (FAHP) to construct a system of evaluation criteria focused on understanding the luxury resort hotels (LRHs) industry in Taiwan and Macao. One finding of this study is that objective hotels in these two territories exhibit different hotel operating characteristic (the unity LRHs mode in Taiwan vs involving casino LRHs in Macao) and customer markets. These Macanese LRHs define them as international operations, in contrast the Taiwanese position themselves as domestic businesses. The other finding is that Taiwan based evaluation criteria on consumer-orientation and operation and management, while Macao stressed evaluation based on operation and management to manage LRHs industry

Developing a hybrid multi-criteria model for investment in stock exchange

One of the main challenges in Stock Market is to choose an appropriate combinations of various assets. The aim of this study is to propose a hybrid method, which is able to survey one problem with some criteria that it is very good for investment problem. In this study, we use a hybrid multiple criteria decision-making (MCDM) model, which shows the dependent relationships among criteria with DEMATEL method to build a relations-structure among criteria. We then use Analytical Network Process (ANP) to determine the relative weights of each criterion with dependence and feedback, and the VIKOR method is implemented to rank and select the best alternatives for investment. This study is in stock exchange in Iran to select the best stocks and the data are gathered through the years (2006-2010). There are a lot of methods to rank and select of firms that most of the methods just do one, ranking or selecting; but the used method in this study not only ranks the firms but also determines which firms (stocks) are best for investment, so that in this study 2 of 50 firms are proposed for investment

Selection of non-financial sustainability indicators as key elements for multi-criteria analysis of hotel chains

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUGNowadays, online information provided by corporate websites has a great impact on the hotel industry performance. According to existing studies, it is very likely that customers' and investors' decisions may change after consulting these portals. The environmental commitment of hotel companies is usually demonstrated to stakeholders by obtaining environmental quality certifications and eco-labels issued by specialised entities in compliance with certain requirements. However, the question of how to use the sustainable indicators that are usually scattered on the web or in company reports is a problemthat requires further research. The main objective of this study is to develop a robust and reliable model to assess the sustainability of hotel chains based on the information gathered from their websites and corporate reports. A literature review is carried out and specialists are consulted to determine the critical factors that affect hotel sustainability. Once the criteria based on nonfinancial indicators have been chosen, they are organised in a hierarchy according to their orientation. To achieve the objective of the study, a hybrid model is proposed that includes two multi-criteria decision-making approaches, namely the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)method. AHP is used to weight the criteria, and the ranking of the alternatives is provided through TOPSIS. Subsequently, a sensitivity analysis is performed to determine the critical indicators. Finally, a numerical example is carried out with a case study of the largest Spanish hotel chains to illustrate the function and applicability of the proposed method. With the results obtained, it has been possible to establish a ranking or selection of hotel chains for the case study, since the hybrid AHP-TOPSIS method provides reliable and robust results for any qualitative or quantitative evaluation criterion, which is of great interest for the different actors involved.Xunta de Galicia | Ref. GRC-202

Risk-based methods for sustainable energy system planning: a review

The value of investments in renewable energy (RE) technologies has increased rapidly over the last decade as a result of political pressures to reduce carbon dioxide emissions and the policy incentives to increase the share of RE in the energy mix. As the number of RE investments increases, so does the need to measure the associated risks throughout planning, constructing and operating these technologies. This paper provides a state-of-the-art literature review of the quantitative and semi-quantitative methods that have been used to model risks and uncertainties in sustainable energy system planning and feasibility studies, including the derivation of optimal energy technology portfolios. The review finds that in quantitative methods, risks are mainly measured by means of the variance or probability density distributions of technical and economical parameters; while semi-quantitative methods such as scenario analysis and multi-criteria decision analysis (MCDA) can also address non-statistical parameters such as socio-economic factors (e.g. macro-economic trends, lack of public acceptance). Finally, untapped issues recognised in recent research approaches are discussed along with suggestions for future research

Proposing a new methodology for prioritising the investment strategies in the private sector of Iran

This article proposes a systematic and organised approach for group decision-making in the presence of the uncertainty involved in expert judgments as used in multi-criteria decision-making (MCDM) issues. This procedure comprises the selection of the optimum alternative with respect to the evaluation criteria under consideration, in particular to select the strategy of investing. However, the selection of the investment strategy is difficult on account of considering the numerous quantitative and qualitative parameters like benefits, opportunities, costs, and risks. However, it is possible that these parameters have a significant influence on each other. A decision-making trial and evaluation laboratory (DEMATEL), used to define the influential network of elements, can be employed to construct a network relationship map (NRM). On the other hand, according to whether the information is incomplete or unavailable, uncertainty is an inseparable part of making decision for solving the MCDM problems. Therefore, this article proposes a new hybrid model based on analytic hierarchical process (AHP), DEMATEL, and echnique for Order of Preference by Similarity to Ideal Solution (TOPSIS) techniques under fuzzy environment to evaluate the problem of the selection of the investment strategy. To achieve the aim, a three-step process is presented to solve a sophisticated problem. First, the AHP method is employed to break down the investment problem into simple structure and calculate the importance weights of criteria by using a pairwise comparison process. Second, the DEMATEL technique is applied for considering interdependence and dependencies and computing the global weights of benefit, opportunities, cost, and risk (BOCR) factors. Finally, the fuzzy TOPSIS methodology is used for prioritising the possible alternatives. To demonstrate the potential application of the proposed model, a numerical example is illustrated and investigated. The results show that the proposed model has a high ability to prioritise the strategies of investing

Multi-criteria decision-making prototype for the 4th construction revolution implementation readiness using intellectual capital perspective

The fourth industrial revolution, so-called Industry 4.0 has transformed the decision-making process by increasing the use of information and digitisation technologies, which resulted in improving the performance and structuring the management process to the industry. Thus, in recent years, the implementation level of information and digitisation technologies in the construction industry, termed as ‘Construction 4.0 (CR4.0)’, has increased rapidly. However, the construction industry has been unable to translate its acquired knowledge into actionable, transformational and strategic goals towards CR4.0. CR4.0 has changed the nature of competitive resources by reshaping the structure and way construction firms work. Construction firms face various technological, human, and process-related challenges. The starting point for this research was based on exploring the potentials in reskilling and upskilling knowledge through the development of Intellectual Capital (IC) of the construction firms. As a result, based on the Resource-based View theory, CR4.0 implementation process has been approached as a knowledge-based innovation which occurred with the development of three IC capitals: Human Capital (HC), Relationship Capital (RC) and Structure Capital (SC ). Hence, this research aims to develop a Multi-Criteria Decision-Making (MCDM) prototype, used to support decision-making in CR4.0 readiness, named as the 'Construction Firm's Industry 4.0 Readiness MCDM (ConFIRM)’. The first objective is to identify the critical criteria of IC that may affect the CR4.0 implementation readiness. The process involved Systematic Literature review and semi-structured interviews. The second objective is to investigate the significant level of IC affecting CR4.0 implementation readiness through Analytical Hierarchy Process (AHP) technique. The third objective is to derive the weightage of criteria and sub-criteria of ConFIRM through Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). The fourth objective is to develop a prototype called as ConFIRM that comprising of 3 main criteria, 16 sub-criteria and 92 super sub-criteria according to their significance weightage in achieving CR4.0 implementation readiness. The MCDM results indicated HC (37%) to be the most critical CR4.0 main criteria, followed by SC (34%), and RC (29%) respectively. The HC represented the cumulative tacit knowledge within the organisation, and it would be the main generator of intangibles. For the sub-criteria level, the results indicated that “Management Capital (12%)” has been considered the most critical CR4.0 sub-criteria. The second most critical sub-criteria would be the “Experience Capital (10%)”, followed by “Process Capital (8%)”. On the other hand, the “Sustainable Capital (2%)” was the least critical sub-criteria. Then, the weightages were formulated into automated MCDM prototype, where the scores were calculated using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), indicating the CR4.0 implementation readiness. As for the fourth objective, ConFIRM was adopted in real case studies and evaluated based on the judgement of five experts to determine its applicability and validity in evaluating CR4.0 readiness of contracting firms in Malaysia. In the case studies, the experts recognised the performance and effectiveness of ConFIRM as the novel method for CR4.0 readiness evaluation. ConFIRM would be able to add value to the development of CR4.0 strategies by identifying the corrective/preventive actions needed, based on the readiness assessment, before the start of the implementation process

Multiple criteria decision analytical tools in assessing risk for green growth: the case of oil palm biomass in Malaysia

The heightening world issues arises from climate change and energy security has created a strong resonance for sustainable development. The utilisation of biomass resources is amongst one of the best strategies to counter carbon emission and energy security issues for waste-to-wealth. Over the last decade, the Malaysian government has shown its clear intent to be a front-runner in the green economy through its various green economy policies and programs, particularly focus on oil palm biomass industry. However, it is observed that the diffusion rate of the industry remains relatively slow as compared to other developing countries such as Thailand and Philippine. Literature, anecdotal evidence, and advocates as well as businesses have identified that one of the non-technical factors that contribute to this problem is financing difficulties. The complication of biomass value chain creation often engaged with high risk profile, capital intensive and long payback period which is unfavourable for financing based on conventional risk assessment. Thus, this research focusses on developing a full range risk assessment model in aiding the industry stakeholder to comprehend the risk profile in managing and mitigating risk in biomass value chain in Malaysia. Multiple decision analytical tools have been employed and developed to integrate non-quantitative factors in risk assessment and design risk mitigation strategy based on the strengths and preferences of different stakeholders’ role. The outputs can serve as policy recommendation to aid the authorities and policy makers to undertake policy reviews to effectively spur the biomass industry for green growth. Furthermore, financier and investor are recommended to utilise the information to enhance its financing decision, to offer financial products that customised the need of sustainable projects without losing great business opportunity. Last but not least, the framework also offers industry stakeholders a practical decision analysis and making tool to integrate preferences as well as quantitative information to mitigate risks before any losses in venturing into the biomass industry occurred

Wind Energy Development Site Selection Using an Integrated Fuzzy ANP-TOPSIS Decision Model

The identification of appropriate locations for wind energy development is a complex problem that involves several factors, ranging from technical to socio-economic and environmental aspects. Wind energy site selection is generally associated with high degrees of uncertainty due to the long planning, design, construction, and operational timescales. Thus, there is a crucial need to develop efficient methods that are capable of capturing uncertainties in subjective assessments provided by different stakeholders with diverse views. This paper proposes a novel multi-criteria decision model integrating the fuzzy analytic network process (FANP) and the fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to evaluate and prioritize the potential sites for wind power development. Four major criteria, namely economic, social, technical, and geographical, with nine sub-criteria are identified based on consultation with wind farm investors, regulatory bodies, landowners and residents, developers and operators, component suppliers, ecologists, and GIS analysts. The stakeholders’ preferences regarding the relative importance of criteria are measured using a logarithmic least squares method, and then the alternative sites are prioritized based on their relative closeness to the positive ideal solution. The proposed model is applied to determine the most appropriate site for constructing an onshore wind power plant consisting of 10 wind turbines of 2.5 MW. Finally, the results are discussed and compared with those obtained using the traditional AHP, ANP and ANP-TOPSIS decision-making approaches